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We are seeking a People Data & Insights Engineer to build and scale the data foundation that powers People Analytics at Takeda. This role sits at the intersection of data engineering and workforce insights, focusing on transforming complex HR and employee experience data into structured and reliable data assets.
This position is embedded within Takeda’s People Analytics and Capabilities team and requires deep engagement with HR use cases such as talent metrics, employee listening, and workforce planning, ensuring data is not only technically sound, but analytically meaningful.
How you will contribute
Design and maintain robust pipelines that integrate HR systems (HRIS, ATS, survey/listening platforms, etc.) into curated, reusable datasets. Build data models that support consistent reporting, longitudinal analysis (e.g., workforce changes over time), and deeper insights into employee experience.
Partner closely with People Analysts and HR stakeholders to understand evolving business questions and embed them into well-designed data models and pipelines.
Implement validation checks, reconciliation logic, and monitoring processes to ensure the integrity of people data across sources and time.
Build and maintain datasets that power consistent reporting across core People Analytics domains (e.g., hiring, retention, mobility, skills, engagement).
Create clear documentation and reusable frameworks to improve how people data is modeled, accessed, and reused across the function.
Apply AI-assisted approaches (e.g., code generation, data exploration, documentation, and troubleshooting) to accelerate development, improve code quality, and streamline pipeline and data model creation.
Skills and qualifications
Bachelor’s degree in a quantitative field (e.g., Data Science, Computer Science, Economics, Analytics) or equivalent experience
~3–6 years of experience in analytics, data engineering, or people analytics
Advanced SQL and experience working with large, complex datasets
Proficiency in Python (or similar) for data processing and automation
Experience with cloud data platforms (e.g., Databricks, Snowflake)
Strong experience designing analytical data models (e.g., dimensional modeling, time-series structures)
Proficiency communicating in English language is mandatory
Experience working with HR data (HRIS, recruiting, survey/listening platforms) or other complex behavioral datasets
Ability to translate ambiguous business questions into structured data solutions
Strong attention to detail and commitment to data quality
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